{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/121995"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/121995","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Nonlinear dependence and its application in finance","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","abstract_has_math":false,"creators":["Xie, Yong"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Mathematics","degree_department":null,"school":null,"contributors":["Linders, Daniel","DeVille, Lee","Sowers, Richard","Verdickt, Gertjan"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-12","date_published":"2023-12","updated_at":"2026-07-22T22:25:00Z","subjects":["Nonlinear Dependence","Asset Pricing","Implied Information","Risk Forecasting","Implied Correlation","Ncertainty Risk"],"languages":["en","eng"],"rights":["Copyright 2023 Yong Xie"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/121995","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Linders, Daniel","DeVille, Lee","Sowers, Richard","Verdickt, Gertjan"]},{"key":"dc:creator","label":"Author","values":["Xie, Yong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-12","2023-11-20"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Nonlinear Dependence","Asset Pricing","Implied Information","Risk Forecasting","Implied Correlation","Ncertainty Risk"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Yong Xie"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/121995"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","The student, Yong Xie, accepted the attached license on 2023-11-17 at 00:05.","The student, Yong Xie, submitted this Dissertation for approval on 2023-11-17 at 00:07.","This Dissertation was approved for publication on 2023-11-20 at 16:13.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19946 on 2024-03-01 at 13:14:45","We explore the implication of nonlinear dependence in the asset pricing theories and risk analytics. Using the Model-Free Implied Dependence (MFID), a measure that exhibits information on linear and nonlinear dependence within the market, we show that stocks with high exposure to MFID generate significantly higher risk-adjusted returns in bad times, which is consistent with time-varying preferences, implying increased demand for assets that offer a hedge in bad times. This finding is robust against other risk common risk factors including implied correlation. Besides, we propose Implied Correlation Gap (ICG) on the top of model-free implied dependence and implied correlation. We demonstrate that ICG is capable of revealing the inadequacy of implied correlation and proxies the degree of nonlinear dependence in the market. More importantly, we document that ICG exhibits incremental predictive power for market uncertainty risks. Our results imply that such predictability is bridged by the investor disagreement."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Nonlinear dependence and its application in finance"]}]}],"canonical_facts":{"dc:contributor":["Linders, Daniel","DeVille, Lee","Sowers, Richard","Verdickt, Gertjan"],"dc:creator":["Xie, Yong"],"dc:date":["2023-12","2023-11-20"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms","The student, Yong Xie, accepted the attached license on 2023-11-17 at 00:05.","The student, Yong Xie, submitted this Dissertation for approval on 2023-11-17 at 00:07.","This Dissertation was approved for publication on 2023-11-20 at 16:13.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19946 on 2024-03-01 at 13:14:45","We explore the implication of nonlinear dependence in the asset pricing theories and risk analytics. Using the Model-Free Implied Dependence (MFID), a measure that exhibits information on linear and nonlinear dependence within the market, we show that stocks with high exposure to MFID generate significantly higher risk-adjusted returns in bad times, which is consistent with time-varying preferences, implying increased demand for assets that offer a hedge in bad times. This finding is robust against other risk common risk factors including implied correlation. Besides, we propose Implied Correlation Gap (ICG) on the top of model-free implied dependence and implied correlation. We demonstrate that ICG is capable of revealing the inadequacy of implied correlation and proxies the degree of nonlinear dependence in the market. More importantly, we document that ICG exhibits incremental predictive power for market uncertainty risks. Our results imply that such predictability is bridged by the investor disagreement."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/121995"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Yong Xie"],"dc:subject":["Nonlinear Dependence","Asset Pricing","Implied Information","Risk Forecasting","Implied Correlation","Ncertainty Risk"],"dc:title":["Nonlinear dependence and its application in finance"],"dc:type":["text"],"thesis:degree_discipline":["Mathematics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:00Z"}